Physical Activity Reduces Gout Risk in Hyperuricemia Patients, Says Machine Learning Study

Results: The RF model outperformed others, achieving a Receiver Operating Characteristic (ROC) of 0.957 in the training cohort and 0.799 in the testing cohort. In the test cohort, it demonstrated an accuracy of 0.778, a Kappa of 0.247, a sensitivity of 0.701, a specificity of 0.785, a positive predictive value of 0.224, a negative predictive value of 0.967, and an F1 score of 0.340. SHAP analysis revealed the following insights: (1) hypertension, serum uric acid, age, gender, and BMI were identified as the top five factors for gout risk; (2) factors such as higher serum uric acid levels, age, BMI, creatinine, sedentary duration, lower PA, hypertension, male sex, and diabetes were associated with an elevated risk of gout; and (3) a PA duration of 1–7 h per week was linked to a lower risk of gout, while sedentary time exceeding 6 h per day increased gout risk, regardless of age, sex, or comorbidities.

They encourage individuals with HUA to engage in 1–7 h of PA per week and limit daily sedentary time to less than 6 h to reduce gout risk. The developed prediction model is freely available as a web-based app at: https://sasuki.shinyapps.io/GoutRisk/.

Reference:

Jiao, Y., Cheng, Z., Lan, Z., Kan, S. and Du, Y. (2025), Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis. Int J Rheum Dis, 28: e70238. https://doi.org/10.1111/1756-185X.70238